2 citations · 3 across the 4 of their papers we have counts for
4 papers
OneRank: Unified Transformer-Native Ranking Architecture for Multi-Task Recommendation
Jiakai Tang, Sunhao Dai, Kun Wang +8
Multi-task learning (MTL) is essential in recommender systems to enable complementary learning among diverse user feedback. While modern industrial practices have shifted from DNNs…
Deploying Semantic ID-based Generative Retrieval for Large-Scale Podcast Discovery at Spotify
Edoardo D'Amico, Marco De Nadai, Praveen Chandar +41
Podcast listening is often grounded in a set of favorite shows, while listener intent can evolve over time. This combination of stable preferences and changing intent motivates rec…
Mining Interest Trends and Adaptively Assigning SampleWeight for Session-based Recommendation
Kai Ouyang, Xianghong Xu, Miaoxin Chen +4
Session-based Recommendation (SR) aims to predict users' next click based on their behavior within a short period, which is crucial for online platforms. However, most existing SR…
Optimizing Audio Recommendations for the Long-Term: A Reinforcement Learning Perspective
Lucas Maystre, Daniel Russo, Yu Zhao
We present a novel podcast recommender system deployed at industrial scale. This system successfully optimizes personal listening journeys that unfold over months for hundreds of m…